Enhanced Analysis Parameter Coverage Guide
PredictRAM Enhanced Analysis Parameter Coverage Guide
This document details specific parameters evaluated by PredictRAM's enhanced analysis system and how to optimize your research reports to receive the highest scores on these metrics.
1. SCORING SYSTEM COMPONENTS
Core Quality Metrics (65% of base composite score)
Factual Accuracy (16%): Correctness and reliability of facts, data points, and claims
Predictive Power (12%): Quality of forecasts, assumptions, and forward-looking assessments
Bias Control (9%): Balanced perspective and objectivity in analysis
Originality (9%): Unique insights beyond consensus views
Risk Disclosure (11%): Comprehensive coverage of potential risks
Transparency (7%): Clarity in methodology, assumptions, and limitations
Enhanced Analysis Metrics (35% of base composite score)
Geopolitical Assessment (9%): Coverage of relevant global, political, and regulatory factors
SEBI Compliance (7%): Adherence to regulatory disclosure requirements
Content Quality (5%): Overall organization, structure, and readability
Content Guidelines Compliance (5%): Following PredictRAM's reporting standards
Stock Quality Assessment (10%): Evaluation of fundamental qualities of covered stocks
Penalty Factors (subtracted from base score)
Plagiarism Penalty: 0-60% reduction based on similarity to existing reports
AI Detection Penalty: 0-40% reduction based on AI-generation probability
2. FACTUAL ACCURACY OPTIMIZATION
Key Elements Evaluated:
Data sources cited
Numerical data presence and accuracy
Financial metrics usage
Verification statements
Data recency
Dos:
Cite at least 5 distinct, verifiable sources (Bloomberg, Reuters, Company Reports)
Include 20+ numerical data points with proper formatting and units
Reference 8+ standard financial metrics (PE, EV/EBITDA, ROE, FCF, etc.)
Include verification phrases ("verified from," "confirmed in," "according to")
Use recent data (within last reporting period)
Cross-reference critical data from multiple sources
Don'ts:
Present opinions as facts
Use outdated information without acknowledgment
Omit sources for key data points
Include suspiciously precise projections
Misrepresent company statements
3. PREDICTIVE POWER OPTIMIZATION
Key Elements Evaluated:
Specificity of forecasts
Methodology explanation
Historical accuracy reference
Assumption transparency
Alternative scenarios
Dos:
Provide explicit price targets with timeframes
Explain methodology in detail (DCF assumptions, multiple justifications)
Reference track record when available
List all major assumptions clearly
Include 3+ scenarios (base/bull/bear) with probabilities
Show sensitivity analysis for key variables
Don'ts:
Make vague, unquantified predictions
Omit key assumptions driving forecasts
Provide price targets without methodology
Ignore macro factors in predictions
Present only one possible outcome
4. BIAS CONTROL OPTIMIZATION
Key Elements Evaluated:
Balanced perspective
Risk acknowledgment
Neutral language
Multiple scenarios
Consideration of opposing views
Dos:
Include balanced perspective phrases ("however," "on the other hand")
Acknowledge 8+ specific risks or challenges
Use neutral language throughout
Present multiple scenarios with balanced probabilities
Address bearish perspectives substantively
Include both positive and negative factors
Don'ts:
Use hyperbolic language ("definitely," "guaranteed")
Ignore or minimize significant risks
Present only bullish scenarios
Dismiss valid bearish arguments
Use emotionally charged language
5. ORIGINALITY OPTIMIZATION
Key Elements Evaluated:
Unique insights
Differentiated perspective
Original analysis methods
Non-consensus views
Value-added content
Dos:
Highlight differentiated views from consensus
Provide unique analytical frameworks
Include proprietary research elements
Offer novel interpretations of common data
Develop original scenarios or theses
Contribute new perspectives on industry trends
Don'ts:
Rehash consensus views without addition
Copy standard industry analyses
Rely exclusively on widely reported information
Follow predictable analytical frameworks
Submit content highly similar to existing reports
6. RISK DISCLOSURE OPTIMIZATION
Key Elements Evaluated:
Risk categorization
Specificity and relevance
Quantification attempts
Balanced coverage
Emerging risk identification
Dos:
Categorize risks (market, execution, regulatory, etc.)
Provide company and industry-specific risks
Quantify potential impacts where possible
Include likelihood and magnitude assessments
Address both short and long-term risks
Include emerging/non-traditional risk factors
Don'ts:
Use generic boilerplate risk statements
Focus only on common/obvious risks
Omit sector-specific regulatory risks
Ignore company-specific vulnerabilities
Fail to distinguish between high/low probability risks
7. TRANSPARENCY OPTIMIZATION
Key Elements Evaluated:
Methodology disclosure
Assumption clarity
Limitation acknowledgment
Opinion/fact distinction
Accessibility of explanation
Dos:
Fully explain all valuation methods used
Clearly state key assumptions
Acknowledge analysis limitations
Distinguish clearly between facts and opinions
Explain technical concepts clearly
Disclose information gaps or uncertainties
Don'ts:
Use unexplained "black box" methodologies
Hide key assumptions
Present estimates as facts
Use unnecessarily complex language
Omit rationale for key judgments
8. GEOPOLITICAL ASSESSMENT OPTIMIZATION
Key Elements Evaluated:
Relevant policy identification
Impact analysis
Cross-border considerations
Regulatory environment assessment
Policy change scenarios
Dos:
Identify specific policies affecting covered companies
Analyze potential regulatory changes with probabilities
Discuss cross-border implications for global companies
Reference recent policy developments or trends
Consider both risks and opportunities from policy shifts
Assess indirect policy impacts on industry dynamics
Don'ts:
Make partisan political statements
Ignore relevant policy developments
Discuss policies without connecting to investment impact
Focus exclusively on domestic factors for global companies
Overstate unlikely extreme scenarios
9. SEBI COMPLIANCE OPTIMIZATION
Key Elements Evaluated:
Registration disclosure
Analyst certification
Conflict of interest disclosure
Company disclaimers
Forward-looking statements disclaimer
Dos:
Include SEBI registration number
Provide standard analyst certification language
Explicitly address conflicts of interest (or absence)
Include appropriate company disclaimers
Add forward-looking statements disclaimer
Follow all current SEBI research analyst guidelines
Don'ts:
Omit any required regulatory disclosures
Use non-standard disclaimer language
Fail to address potential conflicts
Make guarantees about future performance
Ignore Indian market-specific compliance requirements
10. CONTENT QUALITY & GUIDELINES OPTIMIZATION
Key Elements Evaluated:
Organization and structure
Readability and clarity
Appropriate detail level
Adherence to format requirements
Ticker format compliance
Dos:
Follow recommended report structure
Use consistent formatting throughout
Provide appropriate level of detail for report type
Format tickers correctly as [TICKER.NS] or [TICKER.BO]
Use clear section headings and logical flow
Include all required report components
Don'ts:
Submit poorly organized or rambling content
Use inconsistent formatting
Format tickers incorrectly (MUST use brackets)
Submit excessively long or short reports
Omit key sections
11. STOCK QUALITY ASSESSMENT OPTIMIZATION
Key Elements Evaluated:
Fundamental analysis depth
Balance sheet strength assessment
Management quality evaluation
Business model sustainability
Competitive positioning
Dos:
Include comprehensive fundamental analysis
Assess balance sheet strength with specific metrics
Evaluate management track record and capability
Analyze business model sustainability
Discuss competitive advantages/disadvantages
Compare key metrics to sector/industry averages
Don'ts:
Focus only on price action/technicals
Ignore financial health indicators
Omit management assessment
Fail to address competitive threats
Ignore industry disruption risks
12. PENALTY AVOIDANCE STRATEGIES
Plagiarism Penalty Avoidance:
Create original content for each report
Rewrite analyses in your own words
Cite sources properly when using external data
Use unique analytical frameworks
Ensure differentiated perspectives from existing reports
AI Detection Penalty Avoidance:
Edit and refine any AI-assisted drafts thoroughly
Incorporate personal insights and original analysis
Add industry-specific expertise and nuanced judgments
Include proprietary research elements
Ensure natural language flow and analyst voice
13. IMPLEMENTATION CHECKLIST
Before Submission:
Submission Process:
Ensure report is in final form with all sections complete
Submit via the PredictRAM analyst portal or API
The system will extract tickers, analyze content, and generate scores
Enhanced analysis will be available after processing
Review feedback to improve future submissions
14. EXAMPLE SCORE IMPACT
To illustrate the impact of these optimizations, consider:
Base Report:
Limited data sources (2-3)
Generic risk statements
Single scenario analysis
Basic valuation with limited explanation
Missing some SEBI disclosures
Limited geopolitical assessment Typical Score: 0.65-0.70
Optimized Report:
Multiple verified data sources (5+)
Comprehensive, categorized risks
Three detailed scenarios with probabilities
Multiple valuation methods with full explanation
Complete SEBI compliance
Thorough geopolitical assessment Typical Score: 0.85-0.90
The difference between these scores significantly impacts credibility within the platform and visibility to investors.
This guide is intended to help research analysts create high-quality reports that meet PredictRAM's enhanced analysis standards. For platform-specific questions, contact the support team.
Last updated